Literature DB >> 19944441

Spatial variation and source apportionment of water pollution in Qiantang River (China) using statistical techniques.

Fang Huang1, Xiaoquan Wang, Liping Lou, Zhiqing Zhou, Jiaping Wu.   

Abstract

Understanding the spatial distribution and apportioning the sources of water pollution are important in the study and efficient management of water resources. In this work, we considered data for 13 water quality variables collected during the year 2004 at 46 monitoring sites along the Qiantang River (China). Fuzzy comprehensive analysis categorized the data into three major pollution zones (low, moderate, and high) based on national quality standards for surface waters, China. Most sites classified as "low pollution zones" (LP) occurred in the main river channel, whereas those classified as "moderate and high pollution zones" (MP and HP, respectively) occurred in the tributaries. Factor analysis identified two potential pollution sources that explained 67% of the total variance in LP, two potential pollution sources that explained 73% of the total variance in MP, and three potential pollution sources that explained 80% of the total variance in HP. UNMIX was used to estimate contributions from identified pollution sources to each water quality variable and each monitoring site. Most water quality variables were influenced primarily by pollution due to industrial wastewater, agricultural activities and urban runoff. In LP, non-point source pollution such as agricultural runoff and urban runoff dominated; in MP and HP, mixed source pollution dominated. The pollution in the small tributaries was more serious than that in the main channel. These results provide information for developing better pollution control strategies for the Qiantang River. Copyright 2009 Elsevier Ltd. All rights reserved.

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Year:  2009        PMID: 19944441     DOI: 10.1016/j.watres.2009.11.003

Source DB:  PubMed          Journal:  Water Res        ISSN: 0043-1354            Impact factor:   11.236


  27 in total

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4.  Assessment of the environmental significance of nutrients and heavy metal pollution in the river network of Serbia.

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5.  Characterization and source apportionment of water pollution in Jinjiang River, China.

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8.  Extreme weather event may induce Microcystis blooms in the Qiantang River, Southeast China.

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9.  The assessment and prediction of temporal variations in surface water quality-a case study.

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10.  The use of multivariate statistical methods for optimization of the surface water quality network monitoring in the Paraopeba river basin, Brazil.

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